Modeling genotype × environment × management interactions for a sustainable intensification under rainfed wheat cropping system in Morocco

Abstract

Under the conditions of Moroccan rainfed agricultural areas, wheat cropping systems—the population’s basic staple food—are subject to a set of limitations that seasonally impact crop production and farmers’ incomes, thus national food security. In the last decades, the major constraints were often related to the country’s Mediterranean-type climate, through the intense recurrence of drought events and high inter- and intra-annual rainfall fluctuations. Similarly, various forms of soil degradation inhibit the potential of this slowly renewable resource to support wheat crop intensification and ensure livelihoods. However, the limitations sometimes surpass the environmental factors to implicate the inappropriate crop management strategies applied by farmers. In Moroccan rainfed areas, production problems linked to crop management practices result principally from a shortage in the provision of knowledge to Moroccan small farmers, or their indigent economic situation that limits farmers’ capacity to adopt, qualitatively and quantitatively, efficient strategies. Advanced technologies (remote sensing or crop modeling) play key roles in assessing wheat cropping systems in Moroccan rainfed areas. Due to the difficulties of using conventional experience-based agronomic research to understand Genotype × Environment × Management (G × E × M) interactions, the substantial benefits of crop modeling approaches present a better alternative to provide insights. They allow the provision of simpler, rapid, less expensive, deep, and potentially more accurate predictive knowledge and understanding of the status of cropping systems. In the present study, we highlight the constraints that surround wheat cropping systems in Moroccan rainfed conditions. We emphasize the efficiency of applying crop modelling to analyze and improve wheat cropping systems through three main themes: (i) preserving food security, (ii) supporting general adaptation strategies to face climate change effects and extreme events, and (iii) recommending within-season and on-farm crop management advice. Under Moroccan context, crop modeling works have mainly contributed to increase understanding and address the climate change effects on wheat productivity. Likewise, these modeling efforts have played a crucial role in assessing crop management strategies and providing recommendations for general agricultural adaptations specific to Moroccan rainfed wheat.